You want to see if a card dealer is favoring one suit over another. You observe the dealer pick a card, put it back in the deck, shuffle, and then repeat the process 216 times. The results are displayed in the table below. Use an a = 0.10 significance level. %3D a. Complete the rest of the table by filling in the expected frequencies: Frequencies of Suits Dealt Outcome Frequency Expected Frequency Spades 52 Hearts 73 Diamonds 45 Clubs 46 Calculator Scratchwork Area b. What is the correct statistical test to use? Select an answer v C. What are the null and alternative hypotheses? Ho:
You want to see if a card dealer is favoring one suit over another. You observe the dealer pick a card, put it back in the deck, shuffle, and then repeat the process 216 times. The results are displayed in the table below. Use an a = 0.10 significance level. %3D a. Complete the rest of the table by filling in the expected frequencies: Frequencies of Suits Dealt Outcome Frequency Expected Frequency Spades 52 Hearts 73 Diamonds 45 Clubs 46 Calculator Scratchwork Area b. What is the correct statistical test to use? Select an answer v C. What are the null and alternative hypotheses? Ho:
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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I need help with parts d,e,f
![**Chi-Square Test for Goodness of Fit**
You want to see if a card dealer is favoring one suit over another. You observe the dealer pick a card, put it back in the deck, shuffle, and then repeat the process 216 times. The results are displayed in the table below. Use an \(\alpha = 0.10\) significance level.
### a. Complete the rest of the table by filling in the expected frequencies:
#### Frequencies of Suits Dealt
| Outcome | Frequency | Expected Frequency |
|---------|-----------|---------------------|
| Spades | 52 | |
| Hearts | 73 | |
| Diamonds| 45 | |
| Clubs | 46 | |
**Calculator**
**Scratchwork Area**
### b. What is the correct statistical test to use?
\[
\text{Select an answer}
\]
### c. What are the null and alternative hypotheses?
\[
H_0:\
\]
#### Detailed Explanation of the Table
The table above is used to determine if there is a significant preference for any particular suit by the card dealer. The table is comprised of four rows representing the four suits (Spades, Hearts, Diamonds, and Clubs) with their observed frequencies recorded over 216 trials. The last column is for the expected frequencies, which will need to be calculated.
In the absence of any bias from the dealer, each suit should appear approximately equally often. Since there are four suits, the expected frequency for each suit under the null hypothesis would be \( \frac{216}{4} = 54 \).
You are to fill in these expected frequencies as follows:
| Outcome | Frequency | Expected Frequency |
|---------|-----------|---------------------|
| Spades | 52 | 54 |
| Hearts | 73 | 54 |
| Diamonds| 45 | 54 |
| Clubs | 46 | 54 |
### Additional Instructions
You will need to conduct a Chi-Square test for goodness of fit to determine if there is a statistically significant deviation from the expected frequencies.
**Calculator**: This function will be used to perform the computations needed for the test.
**Scratchwork Area**: Use this space to perform any calculations and notes as needed during the test.
**Hypotheses**:
- Null Hypothesis (\(H_0\)):](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ffd16ddfa-c201-4e3f-90ee-e0e9ce8bf5de%2F02bc77a6-1f65-4b1d-a461-2c409ab73791%2Fg05mjzo_processed.jpeg&w=3840&q=75)
Transcribed Image Text:**Chi-Square Test for Goodness of Fit**
You want to see if a card dealer is favoring one suit over another. You observe the dealer pick a card, put it back in the deck, shuffle, and then repeat the process 216 times. The results are displayed in the table below. Use an \(\alpha = 0.10\) significance level.
### a. Complete the rest of the table by filling in the expected frequencies:
#### Frequencies of Suits Dealt
| Outcome | Frequency | Expected Frequency |
|---------|-----------|---------------------|
| Spades | 52 | |
| Hearts | 73 | |
| Diamonds| 45 | |
| Clubs | 46 | |
**Calculator**
**Scratchwork Area**
### b. What is the correct statistical test to use?
\[
\text{Select an answer}
\]
### c. What are the null and alternative hypotheses?
\[
H_0:\
\]
#### Detailed Explanation of the Table
The table above is used to determine if there is a significant preference for any particular suit by the card dealer. The table is comprised of four rows representing the four suits (Spades, Hearts, Diamonds, and Clubs) with their observed frequencies recorded over 216 trials. The last column is for the expected frequencies, which will need to be calculated.
In the absence of any bias from the dealer, each suit should appear approximately equally often. Since there are four suits, the expected frequency for each suit under the null hypothesis would be \( \frac{216}{4} = 54 \).
You are to fill in these expected frequencies as follows:
| Outcome | Frequency | Expected Frequency |
|---------|-----------|---------------------|
| Spades | 52 | 54 |
| Hearts | 73 | 54 |
| Diamonds| 45 | 54 |
| Clubs | 46 | 54 |
### Additional Instructions
You will need to conduct a Chi-Square test for goodness of fit to determine if there is a statistically significant deviation from the expected frequencies.
**Calculator**: This function will be used to perform the computations needed for the test.
**Scratchwork Area**: Use this space to perform any calculations and notes as needed during the test.
**Hypotheses**:
- Null Hypothesis (\(H_0\)):
![### Hypothesis Testing for Distribution Uniformity - Educational Resource
#### Null Hypothesis (\( H_0 \)):
- \[ \] The suits and cards are dependent.
- \[ \] The suits and cards are independent.
- \[ \] The distribution of suits is not uniform.
- \[ \] The distribution of suits is uniform.
#### Alternative Hypothesis (\( H_1 \)):
- \[ \] The distribution of suits is uniform.
- \[ \] The suits and cards are independent.
- \[ \] The suits and cards are dependent.
- \[ \] The distribution of suits is not uniform.
#### Degrees of Freedom Calculation:
- Degrees of freedom (\( d \)) = \[ \]
#### Test Statistic:
- The test statistic for this data = \[ \] (Please show your answer to three decimal places.)
#### P-Value Calculation:
- The p-value for this sample = \[ \] (Please show your answer to four decimal places.)
#### P-Value Comparison:
- The p-value is \[ \] \(\alpha\)
#### Decision Rule:
- Based on this, we should \[ \]
#### Conclusion:
- \[ \] There is sufficient evidence to conclude that the distribution of suits is not uniform.
- \[ \] There is sufficient evidence to conclude that the distribution of suits is uniform.
- \[ \] There is insufficient evidence to conclude that suits and cards are dependent.
- \[ \] There is sufficient evidence to conclude that suits and cards are dependent.
- \[ \] There is insufficient evidence to conclude that the distribution of suits is not uniform.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ffd16ddfa-c201-4e3f-90ee-e0e9ce8bf5de%2F02bc77a6-1f65-4b1d-a461-2c409ab73791%2Ftbv9d16_processed.jpeg&w=3840&q=75)
Transcribed Image Text:### Hypothesis Testing for Distribution Uniformity - Educational Resource
#### Null Hypothesis (\( H_0 \)):
- \[ \] The suits and cards are dependent.
- \[ \] The suits and cards are independent.
- \[ \] The distribution of suits is not uniform.
- \[ \] The distribution of suits is uniform.
#### Alternative Hypothesis (\( H_1 \)):
- \[ \] The distribution of suits is uniform.
- \[ \] The suits and cards are independent.
- \[ \] The suits and cards are dependent.
- \[ \] The distribution of suits is not uniform.
#### Degrees of Freedom Calculation:
- Degrees of freedom (\( d \)) = \[ \]
#### Test Statistic:
- The test statistic for this data = \[ \] (Please show your answer to three decimal places.)
#### P-Value Calculation:
- The p-value for this sample = \[ \] (Please show your answer to four decimal places.)
#### P-Value Comparison:
- The p-value is \[ \] \(\alpha\)
#### Decision Rule:
- Based on this, we should \[ \]
#### Conclusion:
- \[ \] There is sufficient evidence to conclude that the distribution of suits is not uniform.
- \[ \] There is sufficient evidence to conclude that the distribution of suits is uniform.
- \[ \] There is insufficient evidence to conclude that suits and cards are dependent.
- \[ \] There is sufficient evidence to conclude that suits and cards are dependent.
- \[ \] There is insufficient evidence to conclude that the distribution of suits is not uniform.
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